Chatter Control in a Tool–Workpiece Machining System Using an Optimized Tuned Mass Damper

Abstract

Regenerative chatter severely limits productivity in machining operations, and tuned mass dampers (TMDs) are widely used for passive chatter suppression. However, most existing TMD designs neglect workpiece dynamics and rely on two-degree-of-freedom assumptions, leading to suboptimal performance when tool and workpiece dynamics are comparable. This paper presents a three-degree-of-freedom analytical stability model incorporating the coupled dynamics of the cutting tool, workpiece, and TMD. Stability lobes are derived in the frequency domain, and a max–min optimization strategy is proposed to determine optimal TMD parameters across varying workpiece dynamic conditions. The results indicate that variation in workpiece dynamics significantly hinders the improvement in machining stability achieved by the TMD, and its effectiveness is drastically affected when the cutting tool and workpiece have similar dynamic characteristics. To enhance TMD effectiveness in changing workpiece dynamic conditions, tuning parameters should be optimized to reflect these variations. The proposed analytical and optimization framework may provide a basis for future adaptive chatter-control systems that identify changes in tool–workpiece dynamics online and use them to determine appropriate absorber tuning parameters. However, the present study is limited to offline optimization of a passive TMD and does not implement real-time parameter adaptation. Experimental validation using an additively manufactured TMD demonstrates a clear modification of the fundamental dynamic behaviour, wherein the original single resonance is split into two distinct natural frequencies. Though the extent of this frequency separation is marginal, a significant reduction in peak amplitude is observed: 91% in the low-stiffness workpiece and 69.8% in the high-stiffness workpiece, indicating stronger interaction between the absorber and the machining system under compliant conditions.